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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 1 • Date Jan. 2011

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  • Table of contents

    Page(s): C1
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans publication information

    Page(s): C2
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  • Learning From Humans: Agent Modeling With Individual Human Behaviors

    Page(s): 1 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    Multiagent-based simulation (MABS) is a very active interdisciplinary area bridging multiagent research and social science. The key technology to conduct truly useful MABS is agent modeling for reproducing realistic behaviors. In order to make agent models realistic, it seems natural to learn from human behavior in the real world. The challenge presented in this paper is to obtain an individual behavior model by using participatory modeling in the traffic domain. We show a methodology that can elicit prior knowledge for explaining human driving behavior in specific environments, and then construct a driving behavior model based on the set of prior knowledge. In the real world, human drivers often perform unintentional actions, and occasionally, they have no logical reason for their actions. In these cases, we cannot rely on prior knowledge to explain them. We are forced to construct a behavior model with an insufficient amount of knowledge to reproduce the driving behavior. To construct such individual driving behavior model, we take the approach of using knowledge from others to complement the lack of knowledge from the target. To clarify that the behavior model including prior knowledge from others offers individuality in driving behavior, we experimentally confirm that the driving behaviors reproduced by the hybrid model correlate reasonably well with human behavior. View full abstract»

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  • A Generalized Influence Model for Networked Stochastic Automata

    Page(s): 10 - 23
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    The joint dynamics of a collection or network of interacting discrete-time automata can often be described by a single Markov chain. In general, however, analyzing such a chain is computationally intractable for even moderately sized networks because of the explosion in the size of the state space. Asavathiratham introduced the influence model (IM) as a framework for overcoming such limitations. The IM imposes constraints on the update behavior of a network of automata, allowing efficient analysis while still permitting interesting global behavior. However, some of the constraints of the IM are unnecessarily restrictive. The generalized IM (GIM) presented here relaxes some restrictions of the IM, thereby permitting more complex behavior without losing many of the attractive properties of the IM and actually enabling simpler proofs of several results. The GIM is explained and illustrated in relation to the IM from a variety of different perspectives, including geometric. Several examples of GIMs are presented. View full abstract»

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  • People Counting and Human Detection in a Challenging Situation

    Page(s): 24 - 33
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1926 KB) |  | HTML iconHTML  

    Reliable people counting and human detection is an important problem in visual surveillance. In recent years, the field has seen many advances, but the solutions have restrictions: people must be moving, the background must be simple, and the image resolution must be high. This paper aims to develop an effective method for estimating the number of people and locate each individual in a low resolution image with complicated scenes. The contribution of this paper is threefold. First, postprocessing steps are performed on background subtraction results to estimate the number of people in a complicated scene, which includes people who are moving only slightly. Second, an Expectation Maximization (EM)-based method has been developed to locate individuals in a low resolution scene. In this method, a new cluster model is used to represent each person in the scene. The method does not require a very accurate foreground contour. Third, the number of people is used as a priori for locating individuals based on feature points. Hence, the methods for estimating the number of people and for locating individuals are connected. The developed methods have been validated based on a 4-hour video, with the number of people in the scene ranging from 36 to 222. The best result for estimating the number of people has an average error of 10% over 51 test cases. Based on the estimated number of people, some results of the EM-based method have also been shown. View full abstract»

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  • Formalizing Functional Flow Block Diagrams Using Process Algebra and Metamodels

    Page(s): 34 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (471 KB) |  | HTML iconHTML  

    Functional flow block diagrams (FFBDs) are a traditional tool of systems engineering and remain popular in some systems engineering domains. However, their lack of formal definition makes FFBDs imprecise and impossible to rigorously analyze. The inability to analyze FFBDs may allow specification errors to remain undetected until well into the system design process or, worse, until the system is operational. To help address these problems, we have developed a precise formal syntax and semantics for FFBDs, based on the application of metamodels and the process algebra Communicating Sequential Processes (CSP). FFBDs constructed within our formalized framework are precisely defined and amenable to analyses of properties, such as safety, progress, and conformance to required scenarios. We demonstrate some of the analyses made possible by our formalization in a simple case study of system specification and show how our formalization can be used to detect and correct subtle system errors during the specification phase. View full abstract»

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  • Ontology for Developing Web Sites for Natural Disaster Management: Methodology and Implementation

    Page(s): 50 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1122 KB) |  | HTML iconHTML  

    Recent natural disasters have highlighted the need for disaster preparedness, planning, and management. Hurricane Katrina demonstrated the usefulness of Web sites in dealing with natural disasters. However, little is known about the necessary contents and structures of Web-based information systems for natural disaster management. In this paper, we focus on developing an ontology structure of elements for Web-based disaster management systems. Web elements are identified, following a grounded-theory approach, from an inventory of 6032 Web pages drawn from 100 disaster management Web sites. Selected semi-structured data representation approaches are used to organize the resulting ontology structure, which consists of 2094 Web elements. The ontology structure is further coded into a Web-based system, allowing easy online access. View full abstract»

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  • Integration of Decision Analysis and Scenario Planning for Coastal Engineering and Climate Change

    Page(s): 63 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (425 KB) |  | HTML iconHTML  

    This paper develops a methodology for eliciting shifts in preference across future scenarios in the performance assessment of infrastructure policies and investments. The methodology quantifies the robustness of alternative portfolios across a variety of scenarios and identifies the scenarios that greatly affect the assessments. An innovation of the methodology is to elicit, for each scenario, only a few relative increases or decreases in importance of selected terms of the value function, which is more efficient than a full elicitation of the value function for each scenario. The identification of critical scenarios via our methodology can be used to focus resource-intensive and potentially costly modeling activities. The methodology integrates preference orders, centroid weights, and the Borda method. In a demonstration, the methodology assesses the relative sea level and other climate-change scenarios that could affect the performance of coastal protections. View full abstract»

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  • Resource-Transition Circuits and Siphons for Deadlock Control of Automated Manufacturing Systems

    Page(s): 74 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (507 KB) |  | HTML iconHTML  

    The resource-transition circuit ( RTC) and siphon are two different structural objects of Petri nets and used to develop deadlock control policies for automated manufacturing systems. They are related to the liveness property of Petri net models and thus used to characterize and avoid deadlocks. Based on them, there are two kinds of methods for developing deadlock controllers. Such methods rely on the computation of all maximal perfect RTCs and strict minimal siphons (SMSs), respectively. This paper concentrates on a class of Petri nets called a system of simple sequential processes with resources, establishes the relation between two kinds of control methods, and identifies maximal perfect RTCs and SMSs. A graph-based technique is used to find all elementary RTC structures. They are then used to derive all RTCs. Next, an iterative method is developed to recursively construct all maximal perfect RTCs from elementary ones. Finally, a one-to-one correspondence between SMSs and maximal perfect RTCs and, hence, an equivalence between two deadlock control methods are established. View full abstract»

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  • A Credibilistic Approach to Assumption-Based Truth Maintenance

    Page(s): 85 - 96
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (229 KB) |  | HTML iconHTML  

    This paper presents an extension of the assumption-based truth maintenance system (ATMS), called "credibilistic ATMS," which has the capability to cope with uncertain justifications and assumptions. Such justifications and assumptions are represented and dealt with in the framework of credibility theory. Important concepts in ATMS such as environments, labels, logical consequences, and consistency are redefined by the use of credibility measure. Based on these concepts, the label-updating procedure of the classical ATMS is extended, allowing effective computation of the membership function of any node within the network and that of its supporting environment. In addition, the contradictory environments can be captured with respect to their inconsistency degrees. This paper is compared to the most relevant existing research (i.e., ATMS using necessity as the truth value and ATMS using possibility as the truth value), demonstrating the significant improvements made. This paper also presents an illustrative application of credibilistic ATMS in supporting automated construction of domain models. View full abstract»

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  • Optimal Control-Based Strategy for Sensor Deployment

    Page(s): 97 - 104
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (532 KB) |  | HTML iconHTML  

    In sensor network-based detection/surveillance, one of the first challenges to address is the optimal deployment of sensors such that detection requirements are satisfied in a given area. Specifically, we pose the following question: Given a finite number of sensors, what is the best way to deploy these sensors in order to minimize the squared difference between achieved and required detection/miss probabilities? In this paper, we develop a novel optimal control theory based formulation of this sensor deployment problem. Exploiting similarities between the problem at hand and the linear quadratic regulator, an analytical solution is derived and tested. Unlike prior efforts that rely purely on heuristics, the proposed optimal control framework provides a theoretical basis for the resulting solution. As the complexity of the optimal control based solution is high, we develop a low-complexity approximation called Max_Deficiency algorithm. Using simulation results, we show that the proposed algorithms outperform existing methods by using 10% to 30% fewer number of sensors to satisfy detection requirements. View full abstract»

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  • A Framework for Information-Based Sensor Management for the Detection of Static Targets

    Page(s): 105 - 120
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (470 KB) |  | HTML iconHTML  

    A framework is presented for information-theoretic sensor management for the detection of static targets. The sensor manager searches for targets within a cell grid using a suite of sensor platforms. Each sensor platform may contain one or more sensing modalities, and each of these modalities has known probabilities of detection and false alarm and also has an associated cost of use. Additional information such as motion constraints on the sensors and the prior distribution of the targets in space is incorporated. The sensor manager then directs the movement of the sensors through the grid by maximizing the expected information gain that will be obtained with each new sensor observation. Key modeling questions are addressed, including the selection of an appropriate information measure and the joint or independent management of the sensors. Through a number of simulations, the performance of the sensor manager is compared to the performance of a blind sweep procedure, a random search procedure, and an alternative information-theoretic sensor manager. The intelligent sensor management procedure is demonstrated to achieve a superior performance compared to all of the other three techniques. A specific application area for which the sensor management problem is becoming more critical is landmine detection; thus, the performance of the sensor manager is also analyzed using real data from three different landmine detection sensing modalities, and the proposed sensor management technique is again demonstrated to be superior compared to more simplistic approaches. View full abstract»

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  • OWLPath: An OWL Ontology-Guided Query Editor

    Page(s): 121 - 136
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2434 KB) |  | HTML iconHTML  

    Most Semantic Web technology-based applications need users to have a deep background on the formal underpinnings of ontology languages and some basic skills in these technologies. Generally, only experts in the field meet these requirements. In this paper, we present OWLPath, a natural language-query editor guided by multilanguage OWL-formatted ontologies. This application allows nonexpert users to easily create SPARQL queries that can be issued over most existing ontology storage systems. Our approach is a fully fledged solution backed with a proof-of-concept implementation and the empirical results of two challenging use cases: one in the domain of e-finance and the other in e-tourism. View full abstract»

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  • A Generalized Minimal Hitting-Set Algorithm to Handle Diagnosis With Behavioral Modes

    Page(s): 137 - 148
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (322 KB) |  | HTML iconHTML  

    To handle diagnosis with behavioral modes, a new generalized minimal hitting-set algorithm is presented. The key properties in comparison with that of the original minimal hitting-set algorithm given by de Kleer and Williams are that it can handle more than two modes per component and also nonpositive conflicts. The algorithm computes a logical formula that characterizes all diagnoses. Instead of minimal or kernel diagnoses, some specific conjunctions in the logical formula are used to characterize the diagnoses. These conjunctions are a generalization of both minimal and kernel diagnoses. From the logical formulas, it is also easy to derive the set of preferred diagnoses. One usage of the algorithm is fault isolation in the sense of fault detection and isolation (FDI). The algorithm is experimentally shown to provide significantly better performance compared to the fault isolation approach based on structured residuals, which is commonly used in FDI. View full abstract»

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  • Expanding Service Capacities and Increasing Service Reliabilities for the Grid-Based Utility Computing

    Page(s): 149 - 160
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (299 KB) |  | HTML iconHTML  

    A non-polynomial (NP)-hard combinatorial optimization problem that is associated with expanding service capacities and increasing service reliability in grid-based utility computing is investigated in this paper. The considered problem is decomposed into master and slave subproblems, with theoretical justification, and a computationally efficient two-level iterative method that is used in solving it is proposed. To solve the slave subproblem, an ordinal optimization-based n-stage method, associated with an approximate model for objective value evaluation, is employed. To solve the master subproblem, a bisection method is used. Under some conditions, the solution obtained using the proposed iterative two-level method is optimal. The validity of the proposed method is tested by ten cases on a 12-node 17-link computing grid. Five of the ten cases are randomly selected, and the solutions that are obtained in these cases are optimal, rather than “good enough.” The average CPU time required by the proposed method in obtaining the optimal solution of the considered NP-hard combinatorial optimization problem is 2.278 h, when executed using a Pentium IV PC with a 2-GB RAM. Additionally, the computational efficiency of the proposed method greatly exceeds a genetic algorithm with an exact model. View full abstract»

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  • Q-Aura: A Quantitative Model for Managing Mutual Awareness of Smart Social Artifacts

    Page(s): 161 - 168
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (510 KB) |  | HTML iconHTML  

    What if physical artifacts or devices can be aware of each others' physical presence and location, and interact with each other without user intervention or to enable innovative applications? We propose a model for devices to manage awareness of each other, extending a spatial model of interaction previously used in virtual environments. While there has been previous work on cooperative artifacts, our model is unique in introducing a quantitative technique. Moreover, our model is novel in adding to proximity-based interactions among devices the concepts of the following: 1) aura collision types based on relative locations of devices and 2) multiple (adjustable) levels of awareness and concealment measures so that each device can control how much it wants to be aware of others and how much it wants to be concealed from others. Our model is general and supports awareness of devices in (sufficiently) close physical proximity and the right aura sizes. Such devices' awareness of each other facilitates or triggers interaction, and normally precedes interaction among devices (as in human communication). Our model has numerous applications, from smart soft-toy features to proximity-triggered data exchanges. View full abstract»

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  • Nonlinear Programming Model Integrating Different Preference Structures

    Page(s): 169 - 177
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (287 KB) |  | HTML iconHTML  

    In this correspondence paper, we consider a large group decision-making problem in which the decision makers provide their preferences over a number of alternatives using distinct preference structures, including the following: 1) utility values; 2) preference orderings; 3) multiplicative preference relations; 4) incomplete multiplicative preference relations; 5) fuzzy preference relations; and 6) incomplete fuzzy preference relations. We establish a nonlinear programming model to integrate all of these preference structures and then employ a genetic algorithm to find the solution to the problem. This model can be reduced to a variety of special models suitable for group decision-making situations in which the preferences are represented in one (or several) of the aforementioned preference structures. Finally, detailed numerical analysis is provided to verify the feasibility and effectiveness of the model. View full abstract»

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  • Two-Stage Fuzzy Logic Controller for Signalized Intersection

    Page(s): 178 - 184
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (369 KB) |  | HTML iconHTML  

    Traffic efficiency is commonly regarded as the most important target for the control of signalized intersections. However, from the fairness point of view, it can be argued that all vehicles at a signalized intersection should have equal passing opportunities. In this correspondence paper, a two-stage fuzzy logic control model for an isolated signalized intersection has been proposed, where both traffic efficiency and fairness have been considered simultaneously. At the first stage, a green-phase selector has been developed to select the subsequent green phase. At the second stage, a green-time adjustor has been proposed to determine the green time for the selected phase. An offline genetic algorithm (GA) has been developed to optimize the fuzzy rules and membership functions of the two controllers. The simulation results demonstrate that the proposed model outperforms the vehicle-actuated control model and the model proposed by Pappis and Mamdani in 1977 in terms of both traffic efficiency and fairness. The performance of the proposed model can be further improved after its rules and membership functions are optimized by using GA. View full abstract»

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  • Output Feedback Control of Discrete-Time Systems in Networked Environments

    Page(s): 185 - 190
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (171 KB) |  | HTML iconHTML  

    This correspondence paper addresses the problem of output feedback stabilization of control systems in networked environments with quality-of-service (QoS) constraints. The problem is investigated in discrete-time state space using Lyapunov's stability theory and the linear inequality matrix technique. A new discrete-time modeling approach is developed to describe a networked control system (NCS) with parameter uncertainties and nonideal network QoS. It integrates a network-induced delay, packet dropout, and other network behaviors into a unified framework. With this modeling, an improved stability condition, which is dependent on the lower and upper bounds of the equivalent network-induced delay, is established for the NCS with norm-bounded parameter uncertainties. It is further extended for the output feedback stabilization of the NCS with nonideal QoS. Numerical examples are given to demonstrate the main results of the theoretical development. View full abstract»

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  • Online Support Vector Regression With Varying Parameters for Time-Dependent Data

    Page(s): 191 - 197
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    Support vector regression (SVR) is a machine learning technique that continues to receive interest in several domains, including manufacturing, engineering, and medicine. In order to extend its application to problems in which data sets arrive constantly and in which batch processing of the data sets is infeasible or expensive, an accurate online SVR (AOSVR) technique was proposed. The AOSVR technique efficiently updates a trained SVR function whenever a sample is added to or removed from the training set without retraining the entire training data. However, the AOSVR technique assumes that the new samples and the training samples are of the same characteristics; hence, the same value of SVR parameters is used for training and prediction. This assumption is not applicable to data samples that are inherently noisy and nonstationary, such as sensor data. As a result, we propose AOSVR with varying parameters that uses varying SVR parameters rather than fixed SVR parameters and hence accounts for the variability that may exist in the samples. To accomplish this objective, we also propose a generalized weight function to automatically update the weights of SVR parameters in online monitoring applications. The proposed function allows for lower and upper bounds for SVR parameters. We tested our proposed approach and compared results with the conventional AOSVR approach using two benchmark time-series data and sensor data from a nuclear power plant. The results show that using varying SVR parameters is more applicable to time-dependent data. View full abstract»

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  • Special issue on health care management and optimization

    Page(s): 198
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  • Special issue on systems and synthetic biology

    Page(s): 199 - 200
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  • IEEE Systems, Man, and Cybernetics Society Information

    Page(s): C3
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans Information for authors

    Page(s): C4
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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta